Method and apparatus for modular power management and protection of critical services in ambulatory medical devices

ABSTRACT

Architecture and associated methods are provided for power management of ambulatory medical devices. The medical devices is described by a suite of services, each assigned a level of priority (from discretionary to critical), and the power management architecture allows use interchangeable control modules of various levels. A Power Safety Controller supervises the system to ensure appropriate preservation of critical services and provide warnings for low battery level. A Fidelity Controller ensures optimal allocation of power between the different services. A device supervision module estimates device characteristics which can be used by the other levels. The overall architecture ensures a safe and optimal management of services, and allows for a bottom-up deployment of the device.

BACKGROUND OF THE INVENTION

The present invention relates generally to power management of mobiledevices, which are powered by a battery power source. In particular, theinvention relates to power management of a mobile device used to providea medical service, such as measurement of blood glucose levels of adiabetic patient or other physiological monitoring of the patient/user,control of dosing devices such as perfusion pumps, intravenous fluidpumps, transmission of patient monitoring data to a remote center, etc.

Current mobile devices such as cellphones, tablet computers, personaldigital assistants, laptop computers, etc. can be adapted to carry out awide range of functions and perform a wide variety of services. Suchdevices can be enabled with software applications to carry outmedical-related services such as the services mentioned above. Suchdevices are typically battery-powered and thus have a finite operatingtime before the battery goes dead and must be recharged. If the patientis not at a location where the device may be plugged into an electricaloutlet, critical medical services may not be able to be provided. Suchdevices typically have the capability of performing multiple servicessimultaneously, such as cellphone services, email services, music playerservices, video player services, internet browsing, game playing, etc.If such a device is performing a critical medical service to apatient/user of the device while the device also is performing otherservices, battery power will be consumed at a faster rate. Consequentlyit would be desirable to have the ability to reduce or eliminate thepower being consumed by non-critical or non-important services used onsuch a device, when the device also is being used to provide a criticalmedical service for the patient/user, and remaining battery power isapproaching a low level.

SUMMARY OF THE INVENTION

An aspect of an embodiment of the present invention provides, amongother things, architecture and associated methods for power managementof ambulatory medical devices running on battery power. The servicesprovided by the medical devices are described by a suite of services,wherein each service is assigned a level of priority (from discretionaryto critical), and the power management architecture allows aninterchangeable control module to be inserted at multiple controllevels:

-   -   a. Power Safety Control: supervises the system to ensure        appropriate power management to maintain preservation of        critical services and to provide adequate warnings to the user        when remaining power is approaching critical levels.    -   b. Fidelity Controller: ensures optimal allocation of power        between the different services by optimizing performance levels        of various services.    -   c. Device Supervision: estimates device characteristics which        can be used in the other layers.

The overall architecture ensures a safe and optimal management ofservices, and allows for a bottom-up deployment of the device.

In accordance with one embodiment, a power management system formanaging power consumption of a battery-operated device configured toprovide a plurality of services includes a device characteristicsestimation module configured to receive a battery level of said device,at least one parameter of a user of the device, and the services beingprovided by the device, said device characteristics estimation modulebeing further configured to construct time profiles encoding aprobability of at least one of said battery level, user parameter, andservices being provided having certain values at each of a number oftime segment k; a fidelity controller module configured to receive saidtime profiles from said device characteristics estimation module andsaid battery level, and to set a fidelity policy u(k) for each timesegment k, said fidelity policy defining a level of fidelity for eachservice; a power controller module configured to receive said fidelitypolicy u(k) and said battery level, to compute an amount of timeremaining before battery exhaustion under said battery level and a modeof operation having a predefine power consumption rate, and to take apredetermined action based on the computed amount of time remaining withrespect to at least one preset threshold; and a device service regulatormodule for regulating access of said services to resources of saiddevice for performing said services, in accordance with a predeterminedaction communicated from the power controller module.

According to another embodiment, a computer-implemented method formanaging power consumption of a battery-operated device configured toprovide a plurality of services includes performing by a processor:receiving a battery level of said device, at least one parameter of auser of the device, and the services being provided by the device,constructing time profiles encoding a probability of at least one ofsaid battery level, user parameter, and services being provided havingcertain values at each of a number of time segment k; setting a fidelitypolicy u(k) for each time segment k, said fidelity policy defining alevel of fidelity for each service, based on said time profiles andbattery level; computing, based on said time profiles, an amount of timeremaining before battery exhaustion under said battery level and a modeof operation having a predefine power consumption rate, and taking apredetermined action based on the computed amount of time remaining withrespect to at least one preset threshold; and regulating access of saidservices to resources of said device for performing said services, inaccordance with said predetermined action.

According to yet another embodiment, a non-transitory computer-readablestorage medium having stored thereon computer-executable instructions,with respect to managing power consumption of a battery-operated deviceconfigured to provide a plurality of services, causing a computer toperform: receiving a battery level of said device, at least oneparameter of a user of the device, and the services being provided bythe device, constructing time profiles encoding a probability of atleast one of said battery level, user parameter, and services beingprovided having certain values at each of a number of time segment k;setting a fidelity policy u(k) for each time segment k, said fidelitypolicy defining a level of fidelity for each service, based on said timeprofiles and battery level; computing, based on said time profiles, anamount of time remaining before battery exhaustion under said batterylevel and a mode of operation having a predefine power consumption rate,and taking a predetermined action based on the computed amount of timeremaining with respect to at least one preset threshold; and regulatingaccess of said services to resources of said device for performing saidservices, in accordance with said predetermined action.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram showing the various power management controlmodules and their relationships to each other, in accordance with anembodiment of the invention;

FIG. 2 is a diagram showing one example of a power management controland warning scheme in accordance with an embodiment of the invention;

FIG. 3 is a graph illustrating various power consumption scenarios foruse in estimating remaining functional time for a device in accordancewith an embodiment of the invention;

FIG. 4 is a graph illustrating various functions of fidelity levelversus patient risk, which can be used to determine fidelity levels forcritical services as a function of patient risk;

FIG. 5 is a graph illustrating examples of probabilities of activitiesor services being used during various time segments of the day, used toestimate remaining functional time of a device in accordance with anembodiment of the invention; and

FIG. 6 is a block diagram of an exemplary computer system forimplementation of an embodiment of the invention.

DETAILED DESCRIPTION OF THE INVENTION

Formulation:

let {right arrow over (a)}={a_(i)|1=1 . . . n} be the set of installedactivities or services on an ambulatory or mobile device, and{u_(j)=[u_(i,j), u_(2,j), . . . , u_(n,j)]|j=1 . . . m} be the set ofallowed fidelity policies for each activity or service, wherein afidelity policy is associated with a particular power consumption rate.We then propose that for each time segment k, the power remaining x(k+1)can be modeled as

$\begin{matrix}{{{x( {k + 1} )} = {{x(k)} - {{\omega(k)}\mspace{14mu}{where}}}}{\omega(k)} = {\sum\limits_{i = 1}^{n}{f_{i,{u_{i,j}{(k)}}}( {{Ia}_{i}(k)} )}}} & (1.1)\end{matrix}$is the power consumption at stage k, with f_(i,u(k))(Ia_(i)(k)) beingthe power consumption associated with activity a_(i), under the fidelitypolicy u_(j)(k).

Therefore the power consumption can be seen as a stochastic processgoverned by the binomial probability distributions P(Ia_(i)(k)=1) andthe chosen set of fidelity policies at each time segment k.

Architecture

An aspect of an embodiment of the present invention is organized around,for example, a specific architecture of control modules, eachcontrolling one aspect of the power management problem. Thisarchitecture allows for the disambiguation of the control objective(usability versus critical service functionality versus battery life)and its modularity ensures that regardless of the optimal powermanagement strategy chosen, critical services are protected and thedevice is capable of performing its core medical functionalities.

Referring to FIG. 1, the architecture contains control modules at 4levels of increasing abstraction:

-   -   a. The Medical Device Services Regulator (MDSR), which controls        the resource access of all installed services on the device,        wherein service is a set of self-contained software commands        designed to execute a specific action. The MDSR is responsible        for translating the set of policies generated by the power        controller into resource access for the services, potentially        shutting down superfluous or non-critical services. The        installed services are categorized into a plurality of defined        priority levels from critical to discretionary. The MDSR also        provides power level and patient risk information to the Power        Safety Controller (PSC).    -   b. The Power Safety Controller (PSC), which ensures maximum        availability of critical services, i.e. services necessary for        the functioning of the medical device. This module analyzes the        amount of remaining power as communicated from the MDSR,        estimates the amount of operating time remaining, and based on        the estimate may decide to override policies set at higher        levels to ensure priority of critical services over all others        when the battery level gets low. In addition the PSC is        responsible for warning the user of power preservation schemes,        and alerting the user of an imminent power shutdown.    -   c. The Local Fidelity Controller (LFC), which optimizes the        fidelity levels for each of the activities. A fidelity level        defines a level of operation for a service, and corresponds with        a certain power consumption rate. The combination of all        fidelity levels defines the current fidelity policy.    -   d. The Plant Characteristics Estimator (PCE), which observes the        operating state of the device and estimates time-dependent        profiles for activities usage, power consumption for activities        at specific fidelity levels, and patient's risk.

Each level of the architecture runs at a potentially differentfrequency, with the MDSR being run continuously, the PSC being runcontinuously or frequently, the LFC being run intermittently orepisodically, and the PCE being run infrequently or rarely.

Power Safety Controller (PSC)

Overall Design

The power safety controller (PSC) computes the amount of time remainingbefore battery exhaustion under the current battery level and a“critical services only” mode of functioning or power consumption rate.

Based on this assessment of the remaining functional time (rft) andinternally set thresholds for a warning (τ_(w)) and an alert (τ_(a)),the system takes one of three actions, as shown in FIG. 2:

-   -   if rft>τ_(w), the PSC passes through the current power        allocation policy (either preset or output from the local        fidelity controller) to the medical device service regulator        (green light);    -   if rft≦τ_(w) and rft>τ_(a) the PSC preserves power by:        -   stopping discretionary services,        -   lowering fidelity levels of important and critical services,            and        -   warning the user of approaching battery depletion and            activation of the power preservation mode (orange light);    -   if rft<τ_(a), the PSC:        -   stops all non-critical services,        -   lowers the fidelity levels of the critical services,        -   prepares the system for shutdown (data dump, deactivation of            peripheral devices, etc.), and        -   outputs an alarm alerting the user of imminent battery            depletion (red light).            Estimation of the Remaining Functional Time

The PSC can function with a variety of Remaining Functional Time (RFT)estimators. As shown in FIG. 3, four classes of RFT estimator range fromthe least conservative (naïve) to the most conservative (worst casescenario). While classes 1 and 4 are limit cases (naïve and worst casescenario) and do not request additional input from the known consumptionand battery level, cases 2 and 3 require an estimation (or a profileover time) of the risk to the patient, and of the service activitiesbeing used. In FIG. 4, we present an example risk profile where thepatient is particularly at risk in the early afternoon, and an examplebehavior profile where the patient uses her device during her commute toand from work for discretionary activities (e.g. internet, media, games,emails, etc.)

Naïve RFT Estimation

Using the formulation proposed above, a naïe estimation of the RFT isgiven by a simple accounting formula, where x(k) is the remainingbattery life in hours and co is the consumption by hour, and u_(min) isthe policy imposing the lowest fidelity before shut off for allactivities:

$\begin{matrix}{{{rft}(k)} = {{{x(k)}/{w_{c}(k)}}\mspace{14mu}{where}}} & \; \\\{ \begin{matrix}{{w_{c}(k)} = {\sum\limits_{i = 1}^{n}{f_{i,u_{\min}}( {I_{c}a_{i}} )}}} \\{{I_{c}a_{i}} = \{ \begin{matrix}1 & {{if}\mspace{14mu} a_{i}\mspace{14mu}{is}\mspace{14mu}{critical}} \\0 & {otherwise}\end{matrix} }\end{matrix}  & (1.2)\end{matrix}$

Risk Informed RFT Estimation

Risk informed RFT estimation makes use of the estimated medical risk tothe patient in accordance with the risk profile, to estimate the futurepolicies per time segment k: i.e. if the patient's risk is high, thefidelity of critical services will not be lowered, while if the patientis safe it is appropriate to lower the fidelity of critical services.

This can be done either by using the risk profile generated in the upperlayer of the architecture, or by extrapolating the risk at its currentvalues to the time segment under consideration.

In both cases the RFT estimate is

$\begin{matrix}{{{{rft}(k)} = {{argmin}{{{x(k)} - {\sum\limits_{t = 1}^{\tau}{\omega_{c}( {k + t} )}}}}}}{where}\{ \begin{matrix}{{\omega_{c}(k)} = {\sum\limits_{i = 1}^{n}{f_{i,{u{(k)}}}( {I_{c}a_{i}} )}}} \\{{I_{c}a_{i}} = \{ \begin{matrix}1 & {{if}\mspace{14mu} a_{i}\mspace{14mu}{is}\mspace{14mu}{critical}} \\0 & {otherwise}\end{matrix} } \\{{u(k)} = {g( {R(k)} )}}\end{matrix} } & (1.3)\end{matrix}$Here we see that the fidelity level of the critical services isdependent on the estimated patient's risk over time through the functiong. G can be of many forms as shown in FIG. 4, but the key characteristicis that during risky periods the fidelity of the critical services isincreased.

Behaviorally Informed RFT Estimation

In addition to the risk-based assessment of RFT, it is interesting tolook at behavioral profiles to estimate power consumption. Here we thinkin terms especially of multi-use medical devices (such as pump controlor sensor monitoring from cell phones or tablet computers). As thedevice is used for many more things than its critical services (e.g.medical uses) it is important to account for the variability of thepatient's use of these discretionary functions. The upper layer of thearchitecture (Plant Characteristics Estimation) is designed to generateprofiles of use for all activities, therefore enabling accounting for“expected use” in the computation of RFT, as follows:

$\begin{matrix}{{{{rft}(k)} = {{argmin}{{{x(k)} - {\sum\limits_{t = 1}^{\tau}{\omega_{c}( {k + t} )}}}}}}{where}\{ \begin{matrix}{{\omega_{c}(k)} = {\sum\limits_{i = 1}^{n}{{h_{i}(k)}{f_{i,{u{(k)}}}(1)}}}} \\{{u(k)} = {g( {R(k)} )}}\end{matrix} } & (1.4)\end{matrix}$where h_(i)(k) is the probability of activity a_(i) to be used duringtime segment k. Examples of such probability curves are shown in FIG. 5.

Worst Case Scenario RFT Estimation

Using the formulation proposed above, a worst case scenario estimationof the RFT is given by a simple accounting formula, where x(k) is theremaining battery life in hours, co is the consumption by hour, andu_(max) is the policy allowing all services to function at maximumfidelity:

$\begin{matrix}{{{{rft}(k)} = {{x(k)}/{w_{c}(k)}}}{where}{{w_{c}(k)} = {\sum\limits_{i = 1}^{n}{f_{i,u_{\max}}(1)}}}} & (1.5)\end{matrix}$

Local Fidelity Controller

The local fidelity controller (LFC) sets the policy u(k) for each timesegment k. The policy defines the level of fidelity for each activityand can be computed any number of ways. The details of this computationare not part of this invention and thus will not be discussed herein.Such details can be devised by known methods that are not specific tomedical devices. The important consideration is that the system makesavailable to the LFC at each time segment k the battery level, theestimated risk to the patient, and the activities or services being usedby the device. Compatibility with the overall system is achieved byensuring that policies computed through the LFC are translatable by theMDSR.

Plant Characteristics Estimation

The PCE receives from the architecture at each time segment k:

-   -   battery level,    -   the estimated risk to the patient, and    -   the activities being used by the device.

For each input it constructs a time profile, which encodes theprobability of each variable having certain values at each stage k. Suchprofiles can be described over any time span (e.g. one hour, 24 h, 1week,) or even be specific to type of days/week (work, vacation,weekend, etc.)

Commonly available probability distribution estimators can be used toconstruct:

-   -   Activity Profiles,    -   Metabolic Risk Profiles    -   Activity Specific Consumption Profile

Turning to FIG. 6, FIG. 6 is a functional block diagram for a computersystem 600 for implementation of an exemplary embodiment or portion ofan embodiment of present invention. For example, a method or system ofan embodiment of the present invention may be implemented usinghardware, software or a combination thereof and may be implemented inone or more computer systems or other processing systems, such aspersonal digit assistants (PDAs) equipped with adequate memory andprocessing capabilities. In an example embodiment, the invention wasimplemented in software running on a general purpose computer 60 asillustrated in FIG. 6. The computer system 600 may include one or moreprocessors, such as processor 604. The Processor 604 is connected to acommunication infrastructure 606 (e.g., a communications bus, cross-overbar, or network). The computer system 600 may include a displayinterface 602 that forwards graphics, text, and/or other data from thecommunication infrastructure 606 (or from a frame buffer not shown) fordisplay on the display unit 630. Display unit 630 may be digital and/oranalog.

The computer system 600 may also include a main memory 608, preferablyrandom access memory (RAM), and may also include a secondary memory 610.The secondary memory 610 may include, for example, a hard disk drive 612and/or a removable storage drive 614, representing a floppy disk drive,a magnetic tape drive, an optical disk drive, a flash memory, etc. Theremovable storage drive 614 reads from and/or writes to a removablestorage unit 618 in a well known manner. Removable storage unit 618,represents a floppy disk, magnetic tape, optical disk, etc. which isread by and written to by removable storage drive 614. As will beappreciated, the removable storage unit 618 includes a computer usablestorage medium having stored therein computer software and/or data.

In alternative embodiments, secondary memory 610 may include other meansfor allowing computer programs or other instructions to be loaded intocomputer system 600. Such means may include, for example, a removablestorage unit 622 and an interface 620. Examples of such removablestorage units/interfaces include a program cartridge and cartridgeinterface (such as that found in video game devices), a removable memorychip (such as a ROM, PROM, EPROM or EEPROM) and associated socket, andother removable storage units 622 and interfaces 620 which allowsoftware and data to be transferred from the removable storage unit 622to computer system 600.

The computer system 600 may also include a communications interface 624.Communications interface 124 allows software and data to be transferredbetween computer system 600 and external devices. Examples ofcommunications interface 624 may include a modem, a network interface(such as an Ethernet card), a communications port (e.g., serial orparallel, etc.), a PCMCIA slot and card, a modem, etc. Software and datatransferred via communications interface 624 are in the form of signals628 which may be electronic, electromagnetic, optical or other signalscapable of being received by communications interface 624. Signals 628are provided to communications interface 624 via a communications path(i.e., channel) 626. Channel 626 (or any other communication means orchannel disclosed herein) carries signals 628 and may be implementedusing wire or cable, fiber optics, blue tooth, a phone line, a cellularphone link, an RF link, an infrared link, wireless link or connectionand other communications channels.

In this document, the terms “computer program medium” and “computerusable medium” are used to generally refer to media or medium such asvarious software, firmware, disks, drives, removable storage drive 614,a hard disk installed in hard disk drive 612, and signals 628. Thesecomputer program products (“computer program medium” and “computerusable medium”) are means for providing software to computer system 600.The computer program product may comprise a computer useable mediumhaving computer program logic thereon. The invention includes suchcomputer program products. The “computer program product” and “computeruseable medium” may be any computer readable medium having computerlogic thereon.

Computer programs (also called computer control logic or computerprogram logic) are may be stored in main memory 608 and/or secondarymemory 610. Computer programs may also be received via communicationsinterface 624. Such computer programs, when executed, enable computersystem 600 to perform the features of the present invention as discussedherein. In particular, the computer programs, when executed, enableprocessor 604 to perform the functions of the present invention.Accordingly, such computer programs represent controllers of computersystem 600.

In an embodiment where the invention is implemented using software, thesoftware may be stored in a computer program product and loaded intocomputer system 600 using removable storage drive 614, hard drive 612 orcommunications interface 624. The control logic (software or computerprogram logic), when executed by the processor 604, causes the processor604 to perform the functions of the invention as described herein.

In another embodiment, the invention is implemented primarily inhardware using, for example, hardware components such as applicationspecific integrated circuits (ASICs). Implementation of the hardwarestate machine to perform the functions described herein will be apparentto persons skilled in the relevant art(s).

In yet another embodiment, the invention is implemented using acombination of both hardware and software.

In an example software embodiment of the invention, the methodsdescribed above may be implemented in SPSS control language or C++programming language, but could be implemented in other variousprograms, computer simulation and computer-aided design, computersimulation environment, MATLAB, or any other software platform orprogram, windows interface or operating system (or other operatingsystem) or other programs known or available to those skilled in theart.

The invention having been thus disclosed, it will be apparent to thoseskilled in the art that the same may be implemented in many ways withoutdeparting from the spirit and scope of the invention. Any and all suchvariations are intended to be included within the scope of the followingclaims.

REFERENCES

The devices, systems, computer program products, and methods of variousembodiments of the invention disclosed herein may utilize aspectsdisclosed in the following references, applications, publications andpatents and which are hereby incorporated by reference herein in theirentirety:

-   1. European Patent Application Publication No. EP 1 737 099 A1,    Veselic, et al., “Power Management Systems and Methods for a Mobile    Device”, Dec. 27, 2006.-   2. International Patent Application Publication No. WO 2008/070481    A1, Fadell, A., “Power Consumption Management for Functional    Preservation in a Battery-Powered Electronic Device”, Jun. 12, 2008.-   3. European Patent Application Publication No. EP 1 990 887 A1,    Nebon, J., “A Power Management Unit for Battery-Operated Devices”,    Nov. 12, 2008.-   4. International Patent Application Publication No. WO 2006/048838    A1, Maack, H., “Wireless Battery Status Management for Medical    Devices”, May 11, 2006.

The invention claimed is:
 1. A computer-implemented method for managingpower consumption of a battery-operated device configured to provide aplurality of services, comprising, performing by a processor: receivinga battery level of said device, at least one parameter of a user of thedevice, and the services being provided by the device, constructing timeprofiles encoding a probability of at least one of said battery level,user parameter, and services being provided having certain values ateach of a number of time segments k; setting a fidelity policy u(k) foreach time segment k, said fidelity policy defining a level of fidelityfor each service, based on said time profiles and battery level;computing, based on said time profiles, an amount of time remainingbefore battery exhaustion under said battery level and a mode ofoperation having a predefine power consumption rate, and taking apredetermined action based on the computed amount of time remaining withrespect to at least one preset threshold; and regulating access of saidservices to resources of said device for performing said services, inaccordance with said predetermined action.
 2. The method of claim 1,wherein at least one of said services is a critical service beingprovided to said user, said at least one parameter is a risk level ofsaid user with respect to said critical service, said amount of timeremaining is computed based on said risk level of said user, and saidpredetermined action causes maximizing availability of said criticalservice to said user.
 3. The method of claim 2, wherein said amount oftime remaining is computed by the equation: rft(k) = x(k)/w_(c)(k) where$\{ \begin{matrix}{{w_{c}(k)} = {\sum\limits_{i = 1}^{n}{f_{i,u_{\min}}( {I_{c}a_{i}} )}}} \\{{I_{c}a_{i}} = \{ \begin{matrix}1 & {{if}\mspace{14mu} a_{i}\mspace{14mu}{is}\mspace{14mu}{critical}} \\0 & {otherwise}\end{matrix} }\end{matrix} $ where rft(k) is the amount of time remaining attime segment k, x(k) is remaining battery life, and a_(i) is a servicebeing used.
 4. The method of claim 2, wherein said amount of timeremaining is computed by the equation:${{rft}(k)} = {{argmin}{{{x(k)} - {\sum\limits_{t = 1}^{\tau}{\omega_{c}( {k + t} )}}}}}$where $\{ \begin{matrix}{{\omega_{c}(k)} = {\sum\limits_{i = 1}^{n}{f_{i,{u{(k)}}}( {I_{c}a_{i}} )}}} \\{{I_{c}a_{i}} = \{ \begin{matrix}1 & {{if}\mspace{14mu} a_{i}\mspace{14mu}{is}\mspace{14mu}{critical}} \\0 & {otherwise}\end{matrix} } \\{{u(k)} = {g( {R(k)} )}}\end{matrix} $ where rft(k) is the amount of time remaining attime segment k, x(k) is remaining battery life, ω is power consumptionrate, R(k) is a function of said risk of said user, and a_(i) is aservice being used.
 5. The method of claim 2, wherein said amount oftime remaining is computed by the equation:${{{rf}t}(k)} = {{argmin}{{{x(k)} - {\sum\limits_{i = 1}^{\tau}{\omega_{c}( {k + t} )}}}}}$where $\{ \begin{matrix}{{\omega_{c}(k)} = {\sum\limits_{i = 1}^{n}{{h_{i}(k)}{f_{i,{u{(k)}}}(1)}}}} \\{{u(k)} = {g( {R(k)} )}}\end{matrix} $ where rft(k) is the amount of time remaining attime segment k, x(k) is remaining battery life, ω is power consumptionrate, R(k) is a function of said risk of said user, a_(i) is a service,and h_(i)(k) is a probability of service a_(i) to be used during timesegment k.
 6. The method of claim 2, wherein said amount of timeremaining is computed by the equation: rft(k) = x(k)/w_(c)(k) where${w_{c}(k)} = {\sum\limits_{i = 1}^{n}{f_{i,u_{\max}}(1)}}$ where rft(k)is the amount of time remaining at time segment k, and x(k) is remainingbattery life.
 7. A non-transitory computer-readable storage mediumhaving stored thereon computer-executable instructions, with respect tomanaging power consumption of a battery-operated device configured toprovide a plurality of services, causing a computer to perform:receiving a battery level of said device, at least one parameter of auser of the device, and the services being provided by the device,constructing time profiles encoding a probability of at least one ofsaid battery level, user parameter, and services being provided havingcertain values at each of a number of time segments k; setting afidelity policy u(k) for each time segment k, said fidelity policydefining a level of fidelity for each service, based on said timeprofiles and battery level; computing, based on said time profiles, anamount of time remaining before battery exhaustion under said batterylevel and a mode of operation having a predefine power consumption rate,and taking a predetermined action based on the computed amount of timeremaining with respect to at least one preset threshold; and regulatingaccess of said services to resources of said device for performing saidservices, in accordance with said predetermined action.
 8. Thenon-transitory computer-readable storage medium of claim 7, wherein atleast one of said services is a critical service being provided to saiduser, said at least one parameter is a risk level of said user withrespect to said critical service, said amount of time remaining iscomputed based on said risk level of said user, and said predeterminedaction causes maximizing availability of said critical service to saiduser.
 9. The non-transitory computer-readable storage medium of claim 8,wherein said amount of time remaining is computed by the equation:rft(k) = x(k)/w_(c)(k) where $\{ \begin{matrix}{{w_{c}(k)} = {\sum\limits_{i = 1}^{n}{f_{i,u_{\min}}( {I_{c}a_{i}} )}}} \\{{I_{c}a_{i}} = \{ \begin{matrix}1 & {{if}\mspace{14mu} a_{i}\mspace{14mu}{is}\mspace{14mu}{critical}} \\0 & {otherwise}\end{matrix} }\end{matrix} $ where rft (k) is the amount of time remaining attime segment k, x(k) is remaining battery life, and a_(i) is a servicebeing used.
 10. The non-transitory computer-readable storage medium ofclaim 8, wherein said amount of time remaining is computed by theequation:${{rft}(k)} = {{argmin}{{{x(k)} - {\sum\limits_{t = 1}^{\tau}{\omega_{c}( {k + t} )}}}}}$where $\{ \begin{matrix}{{\omega_{c}(k)} = {\sum\limits_{i = 1}^{n}{f_{i,{u{(k)}}}( {I_{c}a_{i}} )}}} \\{{I_{c}a_{i}} = \{ \begin{matrix}1 & {{if}\mspace{14mu} a_{i}\mspace{14mu}{is}\mspace{14mu}{critical}} \\0 & {otherwise}\end{matrix} } \\{{u(k)} = {g( {R(k)} )}}\end{matrix} $ where rft(k) is the amount of time remaining attime segment k, x(k) is remaining battery life, ω is power consumptionrate, R(k) is a function of said risk of said user, and a_(i) is aservice being used.
 11. The non-transitory computer-readable storagemedium of claim 8, wherein said amount of time remaining is computed bythe equation:${{r{ft}}(k)} = {{argmin}{{{x(k)} - {\sum\limits_{t = 1}^{\tau}{\omega_{c}( {k + t} )}}}}}$where $\{ \begin{matrix}{{\omega_{c}(k)} = {\sum\limits_{i = 1}^{n}{{h_{i}(k)}{f_{i,{u{(k)}}}(1)}}}} \\{{u(k)} = {g( {R(k)} )}}\end{matrix} $ where rft(k) is the amount of time remaining attime segment k, x(k) is remaining battery life, ω is power consumptionrate, R(k) is a function of said risk of said user, a_(i) is a service,and h_(i)(k) is a probability of service a_(i) to be used during timesegment k.
 12. The non-transitory computer-readable storage medium ofclaim 8, wherein said amount of time remaining is computed by theequation: rft(k) = x(k)/w_(c)(k) where${w_{c}(k)} = {\sum\limits_{i = 1}^{n}{f_{i,u_{\max}}(1)}}$ where rft(k)is the amount of time remaining at time segment k, and x(k) is remainingbattery life.